Purpose This article aims to demonstrate how haptic feedback plays a critical role in enhancing control and precision in vision-assisted teleoperation, yet current systems are either costly, hardware-intensive or limited to basic binary cues. This work addresses that gap by proposing a novel, cost-effective framework that integrates computer vision with real-time, graded vibrotactile feedback for intuitive user guidance. Design/methodology/approach The system uses OpenCV-based contour tracking to compare stored and incoming shapes, triggering haptic feedback only during meaningful interactions. Unlike edge-triggered or force-feedback systems, this method provides continuous, interaction-based tactile cues via a vibration motor controlled by an Arduino Mega 2560. A Novint Falcon stylus serves as the user interface. By prioritizing lightweight, deterministic algorithms and minimizing per-frame computations, the streamlined pipeline avoids deep learning networks or high-bandwidth force-feedback loops, ensuring low end-to-end latencies for responsive and reproducible guidance. Findings Experiments show the system significantly improves tracking accuracy and task efficiency, reducing trajectory deviation and completion time by up to 50% for square paths. Although benefits were smaller for circular paths, graded PWM-based feedback improved alignment and user stability. Root mean square error and lag analysis confirmed enhanced master–slave coordination and responsiveness. Users reported smoother and more intuitive control under graded feedback compared to binary or no-feedback modes. Practical implications This system offers a cost-effective, modular solution for real-time haptic feedback in vision-guided teleoperation, using off-the-shelf hardware and open-source software. Its simplicity, affordability (under 500) and sub-100 ms response time makes it highly scalable for applications in remote training, assistive robotics, rehabilitation and low-cost industrial inspection. Unlike expensive force-feedback systems, our platform provides intuitive tactile interaction using compact, portable components. Its commercial potential lies in enabling accessible haptic technology for education, VR interfaces and telehealth markets. With further refinement, such as multi-motor feedback or 3D vision integration, this platform can support a new class of intelligent, affordable human-machine interfaces. Originality/value This work introduces a scalable, low-cost approach to continuous haptic guidance without relying on high-end hardware or machine learning. Its modular design, real-time performance and vision-driven interaction make it well suited for applications in industrial inspection, surgical training and rehabilitation, offering a practical advancement toward accessible haptic teleoperation systems.
Sirwal et al. (Thu,) studied this question.